A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

Journal: Journal of neuroscience methods
Published Date: Sep 2, 2018

Abstract

BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging.

Authors

  • Md Ashad Alam
    Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118, USA. Electronic address: malam@tulane.edu.
  • Hui-Yi Lin
    Department of Biostatistics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
  • Hong-Wen Deng
    Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA 70112, USA.
  • Vince D Calhoun
    Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico; Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, New Mexico; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico; Department of Neurosciences, University of New Mexico, Albuquerque, New Mexico.
  • Yu-Ping Wang
    School of Science and Engineering and School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.

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